DeepChat - Open-Source Local-First AI Agent Desktop Client

DeepChat is an open-source, local-first AI agent desktop client with rich agent capabilities, designed around the Tape.systems philosophy, with support for MCP, Skills, ACP, and remote control integrations for messaging apps.

❤️ Sponsor

	Thanks to APIMart for sponsoring this project! APIMart is a low-cost API platform for AI image & video generation — GPT-Image-2 from $0.006/image, 160+ images per dollar. One async API covers both image and video: submit a task, get an ID, fetch results via polling or callback. Batch tens of thousands of images without timeouts, switch models without changing code. Pay-as-you-go with no monthly fee — sign up here to get started.
	Thanks to OpenModel for sponsoring this project! OpenModel offers client-specific discounts of up to 90% for Codex and 60% for Claude Code across supported models, helping developers cut API costs without changing how they work. Just connect your OpenModel API key and keep using Codex or Claude Code as usual — supported clients are detected automatically and discounted routes are applied with no extra parameters or manual routing required. You can also configure fallback behavior per API key, choosing whether to continue at standard pricing or stop when a discounted route is temporarily unavailable. DeepChat users can register via this link.
	PackyCode is a stable, high-performance API relay provider, offering relay services for Claude Code, Codex, Gemini, and more. With automatic failover, smart routing, and unlimited concurrency, it turns AI into a real productivity tool. Register via this link and get started!

📑 Table of Contents

• 📑 Table of Contents
• 🚀 Project Introduction
• 💡 Why Choose DeepChat
• 🔥 Main Features
• 📼 Tape & Trace
• 🧠 Skills Support
• 🧩 ACP Integration (Agent Client Protocol)
• 📡 Remote Control
• 🤖 Supported Model Providers
  • Compatible with any model provider in OpenAI/Gemini/Anthropic API format
• 🔍 Use Cases
• 📦 Quick Start
  • Download and Install
  • Configure Models
  • Start Conversations
• 💻 Development Guide
  • Install Dependencies
  • Start Development
  • Build
• 👥 Community & Contribution
• ⭐ Star History
• 👨‍💻 Contributors
• 📃 License

🚀 Project Introduction

DeepChat is a powerful open-source, local-first AI agent desktop client that brings together models, tools, Skills, agent runtimes, Tape, and long-running sessions in one desktop app. Whether you're using cloud APIs like OpenAI, Gemini, Anthropic, or locally deployed Ollama models, DeepChat delivers a smooth user experience.

DeepChat's sessions and agent processes follow the Tape.systems philosophy: keep the process, so context, tool calls, requests, and results stay recoverable, traceable, and inspectable. It also provides strong MCP support, installable Skills, ACP agent integration, and remote control for Telegram, Feishu/Lark, QQBot, Discord, WeChat iLink, and other messaging workflows.

💡 Why Choose DeepChat

Compared to other AI tools, DeepChat offers the following unique advantages:

• Local-First Agent Desktop Client: Run DeepChat agents, ACP agents, and remote-ready bots in one local app
• Tape.systems Philosophy: Preserve recoverable session history, trace request context, and inspect token budgets when agent work gets complex
• Skills That Travel: Install, import, export, and enable reusable Skills per conversation for code review, documents, frontend work, Office/PDF tasks, and more
• Native ACP Integration: Run ACP-compatible coding and task agents as first-class entries in the model selector
• Strong MCP Support: Support Resources, Prompts, Tools, multiple transports, inMemory services, and one-click installation
• Remote-Ready Workflows: Control DeepChat sessions from Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink
• Unified Multi-Model Management: One application supports mainstream cloud LLMs and local Ollama models, eliminating the need to switch between multiple apps
• Privacy-Focused: Local data storage and network proxy support reduce the risk of information leakage
• Business-Friendly: Embraces open source under the Apache License 2.0, suitable for both commercial and personal use

🔥 Main Features

• 🤖 Local-First Agent Desktop Client
  • Select DeepChat, ACP, and remote-capable agents from one model-like entry point
  • Run long-lived sessions with project folders, permission modes, tool output, and resumable context
• 📼 Tape & Trace
  • Session Tape records structured work history for recovery, resume, and future agent memory flows
  • Trace previews show request sequences, provider/model metadata, Tape view manifests, included entries, and token budgets
• 🧠 Skills
  • Install Skills from folders, ZIP files, or URLs
  • Enable Skills per conversation so DeepChat can load task-specific instructions, references, and optional scripts
  • Import and export Skills with Claude Code, Codex, Cursor, Windsurf, GitHub Copilot, and other compatible tools
• 🤝 ACP (Agent Client Protocol) Agent Integration
  • Run ACP-compatible agents (built-in or custom commands) as selectable “models”
  • ACP workspace UI for structured plans, tool calls, and terminal output when provided by the agent
• 📡 Remote Control
  • Control DeepChat sessions from Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink
  • Bind remote endpoints to sessions, switch models, answer pending interactions, stop runs, and open desktop sessions remotely
• 🌐 Multiple Cloud LLM Provider Support: DeepSeek, OpenAI, Moonshot/Kimi, Grok, Gemini, Anthropic, and more
• 🏠 Local Model Deployment Support:
  • Integrated Ollama with comprehensive management capabilities
  • Control and manage Ollama model downloads, deployments, and runs without command-line operations
• 🚀 Rich and Easy-to-Use Chat Capabilities
  • Complete Markdown rendering with code block rendering based on industry-leading CodeMirror
  • Multi-window + multi-tab architecture supporting parallel multi-session operations across all dimensions, use large models like using a browser, non-blocking experience brings excellent efficiency
  • Supports Artifacts rendering for diverse result presentation
  • Messages support retry to generate multiple variations; conversations can be forked freely, ensuring there's always a suitable line of thought
  • Supports rendering images, Mermaid diagrams, and other multi-modal content; supports GPT-4o, Gemini, Grok text-to-image capabilities
  • Supports highlighting external information sources like search results within the content
• 🔍 Robust Search Extension Capabilities
  • Built-in integration with leading search APIs like BoSearch and Brave Search, allowing the model to intelligently decide when to search
  • Supports mainstream search engines like Google, Bing, Baidu, and Sogou Official Accounts search by simulating user web browsing, enabling the LLM to read search engines like a human
  • Supports reading any search engine; simply configure a search assistant model to connect various search sources, whether internal networks, API-less engines, or vertical domain search engines, as information sources for the model
• 🔧 Strong MCP (Model Context Protocol) Support
  • Full support for Resources / Prompts / Tools
  • Supports StreamableHTTP, SSE, Stdio, and other transports
  • Official Node.js toolchain for npx/node-style services, installed from Settings when needed
  • inMemory services for code execution, web information retrieval, file operations, and other common utilities
  • Clear tool-call display with parameter and return-data debugging
  • DeepLink support for one-click MCP service installation
• 💻 Multi-Platform Support: Windows, macOS, Linux
• 🎨 Beautiful and User-Friendly Interface, user-oriented design, meticulously themed light and dark modes
• 🔗 Rich DeepLink Support: Initiate conversations via links for seamless integration with other applications, including one-click MCP service installation.
• 🚑 Security-First Design: Chat data and configuration data have reserved encryption interfaces and code obfuscation capabilities
• 🛡️ Privacy Protection: Supports screen projection hiding, network proxies, and other privacy protection methods to reduce the risk of information leakage
• 💰 Business-Friendly:
  • Embraces open source, based on the Apache License 2.0 protocol, enterprise use without worry
  • Enterprise integration requires only minimal configuration code changes to use reserved encrypted obfuscation security capabilities
  • Clear code structure, both model providers and MCP services are highly decoupled, can be freely customized with minimal cost
  • Reasonable architecture, data interaction and UI behavior separation, fully utilizing Electron's capabilities, rejecting simple web wrappers, excellent performance

For more details on how to use these features, see the documentation index.

📼 Tape & Trace

DeepChat's session Tape follows the Tape.systems philosophy and keeps agent work recoverable and inspectable. Trace previews expose request sequences, provider/model metadata, Tape view manifests, included or excluded entries, and token budgets, making long-running agent sessions easier to debug and resume.

🧠 Skills Support

DeepChat Skills are designed to be compatible with the standard Agent Skills specification. A Skill can include task instructions, reference files, assets, and optional scripts, so DeepChat can act more like a domain specialist after it is enabled.

You can install Skills from folders, ZIP files, or URLs, and import/export them with Claude Code, Codex, Cursor, Windsurf, GitHub Copilot, Kiro, Antigravity, OpenCode, Goose, Kilo Code, and other compatible tools.

Built-in Skills cover generative art, code review, DeepChat settings, document collaboration, DOCX, frontend design, git commit messages, infographic syntax, MCP building, PDF, PPTX, Skill creation, Web Artifacts, and XLSX workflows.

Quick start:

1. Open Settings → Skills
2. Install or import a Skill
3. Enable it in conversations that need that capability

🧩 ACP Integration (Agent Client Protocol)

DeepChat has built-in support for Agent Client Protocol (ACP), allowing you to integrate external agent runtimes into DeepChat with a native UI. Once enabled, ACP agents appear as first-class entries in the model selector, so you can use coding agents and task agents directly inside DeepChat.

Quick start:

1. Open Settings → ACP Agents and enable ACP
2. Enable a built-in ACP agent or add a custom ACP-compatible command
3. Select the ACP agent in the model selector to start an agent session

To explore the ecosystem of compatible agents and clients, see: https://agentclientprotocol.com/overview/clients

📡 Remote Control

DeepChat can be controlled from messaging apps, so you can keep a session running even when you are away from the desktop. Configure remote channels under Settings → Remote.

Supported channels include Telegram, Feishu/Lark, QQBot, Discord, and WeChat iLink. Remote endpoints can bind to one DeepChat session, then create new sessions, list and switch recent sessions, stop generation, open the current session on desktop, answer pending questions or permission prompts, switch models, and check runtime status.

Common commands include /start, /help, /pair, /new, /sessions, /use, /stop, /open, /pending, /model, and /status.

🤖 Supported Model Providers

Deepseek	Moonshot	OpenAI	Gemini
Ollama	Qiniu	New API	Grok
Zhipu	PPIO	MiniMax	Fireworks
AIHubMix	Doubao	DashScope	Groq
JieKou.AI	ZenMux	GitHub Models	LM Studio
Hunyuan	302.AI	Together	Poe
Vercel AI Gateway	OpenRouter	Azure OpenAI	TokenFlux
BurnCloud	OpenAI Responses	CherryIn	ModelScope
AWS Bedrock	Voice.ai	Vertex AI	GitHub Copilot
Xiaomi	o3.fan	Novita AI	Astraflow
Anthropic	SiliconFlow